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Improving the taxonomy of fossil pollen using convolutional neural networks and superresolution microscopy. | LitMetric

AI Article Synopsis

  • Taxonomic resolution in palynology (the study of pollen) is tough, hindering the understanding of ancient ecological and evolutionary data from fossil pollen.
  • This study introduces a new method using optical superresolution microscopy and machine learning to enhance fossil pollen analysis, resulting in a more efficient way to identify pollen types.
  • Three different convolutional neural network models were developed and trained, achieving high accuracy in classifying both modern and fossil pollen, supporting theories about the origin and dispersal of certain legume genera in ancient Africa and South America.

Article Abstract

Taxonomic resolution is a major challenge in palynology, largely limiting the ecological and evolutionary interpretations possible with deep-time fossil pollen data. We present an approach for fossil pollen analysis that uses optical superresolution microscopy and machine learning to create a quantitative and higher throughput workflow for producing palynological identifications and hypotheses of biological affinity. We developed three convolutional neural network (CNN) classification models: maximum projection (MPM), multislice (MSM), and fused (FM). We trained the models on the pollen of 16 genera of the legume tribe Amherstieae, and then used these models to constrain the biological classifications of 48 fossil specimens from the Paleocene, Eocene, and Miocene of western Africa and northern South America. All models achieved average accuracies of 83 to 90% in the classification of the extant genera, and the majority of fossil identifications (86%) showed consensus among at least two of the three models. Our fossil identifications support the paleobiogeographic hypothesis that Amherstieae originated in Paleocene Africa and dispersed to South America during the Paleocene-Eocene Thermal Maximum (56 Ma). They also raise the possibility that at least three Amherstieae genera (, , and ) may have diverged earlier in the Cenozoic than predicted by molecular phylogenies.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668113PMC
http://dx.doi.org/10.1073/pnas.2007324117DOI Listing

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